Image Enhancement Technology in Pavement Disease Detection System | |
Li, Xuefeng1; Zhou, Zuofeng2; Wu, Qingquan2 | |
2022 | |
会议名称 | 2nd IEEE International Conference on Electronic Technology, Communication and Information, ICETCI 2022 |
会议录名称 | 2022 IEEE 2nd International Conference on Electronic Technology, Communication and Information, ICETCI 2022 |
页码 | 547-549 |
会议日期 | 2022-05-27 |
会议地点 | Changchun, China |
出版者 | Institute of Electrical and Electronics Engineers Inc. |
产权排序 | 1 |
摘要 | Efficient pavement bad location detection and repair is essential to prolong the use time of roads. However, traditional manual detection methods are extremely inefficient and can no longer meet the requirements of inspecting a large number of roads. When using deep learning technology for road disease detection, it is found that low-illuminance images will affect the detection accuracy due to low contrast. Therefore, before training and testing the deep learning model, the original image needs to be preprocessed to improve the image quality. First, bilateral filtering is used instead of Gaussian filtering to estimate the illuminance of the original image; Then the reflection component is get according to the principle of Retinex algorithm, and the reflection image is quantized; Finally, the image is subjected to illumination compensation. The results of comparative experiments display that the ours algorithm can retain the characteristic details of road diseases and eliminate the unevenness of the image brightness distribution while improving the contrast of the road image. © 2022 IEEE. |
关键词 | pavement diease retinex image enhancement |
作者部门 | 飞行器光学成像与测量技术研究室 |
DOI | 10.1109/ICETCI55101.2022.9832258 |
收录类别 | EI |
ISBN号 | 9781728181158 |
语种 | 英语 |
EI入藏号 | 20223312571189 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/96123 |
专题 | 飞行器光学成像与测量技术研究室 |
通讯作者 | Zhou, Zuofeng |
作者单位 | 1.Xi'an Institute of Optics and Precision Mechanics, Cas, University of Chinese Academy of Sciences, Beijing, China; 2.Xi'an Institute of Optics and Precision Mechanics, Cas, Industrial Development Co., Ltd, Xi'an, China |
推荐引用方式 GB/T 7714 | Li, Xuefeng,Zhou, Zuofeng,Wu, Qingquan. Image Enhancement Technology in Pavement Disease Detection System[C]:Institute of Electrical and Electronics Engineers Inc.,2022:547-549. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Image Enhancement Te(787KB) | 会议论文 | 限制开放 | CC BY-NC-SA | 请求全文 |
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